Campus News

UGA geneticist receives NIH award to pursue precision medicine

University of Georgia researcher Kaixiong Ye has received a Maximizing Investigators Research Award from the National Institutes of Health. The nearly $2 million, five-year award will support efforts to characterize gene-environment interactions, or genetic effects modified by environment, underlying complex traits in humans.

The MIRA is a grant to provide support for a program of research in an early-stage investigator’s laboratory that falls within the mission of National Institute of General Medical Sciences, which supports basic research that increases our understanding of biological processes and lays the foundation for advances in disease diagnosis, treatment, and prevention.

Ye’s lab will develop statistical tests to identify historical genetic responses to the Agricultural Revolution during human evolution, to inform an understanding and study of the current epidemics of complex diseases, likely the result of gene-lifestyle mismatches.

“Genetic variations, environmental factors, and their interactions underlie the etiology of all human diseases, such as obesity and heart diseases,” said Ye, an assistant professor in the Franklin College of Arts and Sciences’ genetics department. “While many studies have identified specific genetic variations and environmental factors associated with a disease, few studies examine their interactions – how the same environmental factor has different effects on a disease in individuals with different genetic backgrounds.”

The work will build on existing investigations by Ye’s lab, including a recent study published in PLOS Genetics that found the effect of fish oil supplementation in reducing blood triglycerides is much stronger in individuals with a specific genotype.

“These kinds of findings will inform the customization of dietary and clinical interventions to one’s genetic background. This is one of the promises of Precision Medicine,” Ye said.

Current patterns of genetic variations in human populations are results of many years of human evolution, during which mutations adaptive to local environment became more common in the population. Historical genetic adaptations to local environment forged unique gene-environment matching relationships, providing evolutionary insights into how to match our lifestyles to genetic background in order to prevent diseases.

Leveraging access to the growing volume of ancient DNA, Ye’s team will first develop and apply statistical tests to identify genetic and polygenic responses to the Agricultural Revolution. To directly identify and quantify gene-environment interactions in complex traits, the lab will develop an efficient computational pipeline and perform large-scale interaction analysis across the genome, phenome, and selected high-quality environmental factors in UK Biobank. All summary statistics will be released publicly as a database on a dedicated website to fuel further explorations, such as meta-analysis and testing for replicability across cohorts and ancestries.

“Dr. Ye was hired to expand our departmental expertise into human genetics. His research approach was particularly attractive to us because it integrates human genetics and evolution to address current problems in human health and society,” said Nancy Manley, Distinguished Research Professor and head of the department of genetics. “We couldn’t be more pleased at this award, which is richly deserved, and will propel his research forward into new and exciting directions.”

“UGA is especially strong in evolutionary genetics and computational biology, with many excellent faculty members working on these areas, attracting outstanding graduate students and postdocs to the university,” Ye said. “With these capabilities in the department of genetics and the Institute of Bioinformatics, we will develop computational tools and perform large-scale empirical analysis in large population cohorts to characterize gene-environment interactions, to prioritize actionable environmental exposures for clinical intervention, and to improve genetic prediction for precision medicine.”